About me
Hello! I am a Ph.D. student in Computer Science at Georgetown University located in Washington, DC. I am working with Prof. Lisa Singh on Data Science, Social Media Mining and NLP.
Most of my projects are collaborations with CNN, Washington Post, UMich and MDI on leveraging AI/ML methods for data-centric social concerns such as sentiment analysis, stance detection, force-migration, gun policy, MeToo movement, spam, misinformation and fake news. I spent some time working at 
Twitter and 
Google.
News
- One paper accepted at ECML 2022 (to appear).
- I passed my PhD proposal defense 🎉
- Three papers accepted at Machine Learning, LREC 2022, and DATA 2022.
- I join Twitter as an ML intern.
- Our paper has been accepted at
The Harvard Misinformation Review. - I served as a reviewer at EMNLP 2021, ACL 2022 and ICWSM 2023.
I joined
Google Cloud AI as a PhD intern.- Our paper has been accepted as a long paper at NAACL 2021.
- Our project with
known as The Breakthrough is reported weekly on CNN Politics. - Our paper has been published in the Journal of Computational Social Science.
- Our work about COVID-19 misinformation was reported on
Washington Post. - Started building this web page.
Interests
- AI, ML, Data Science
- Natural Language Processing
- Data-Efficient Learning
- Misinformation / Fake News
Education
-
PhD in Computer Science, 2017 - present
Georgetown University
-
BEng in Computer Engineering, 2012 - 2016
Chulalongkorn University
Skills
Python
Machine Learning
Data Science
Experience
Machine Learning Intern
- Leverage AI/ML to improve Twitter.
- Conduct and deploy end-to-end machine learning pipelines from research to production.
Software Engineer Intern (AI/ML)
- Research, experiment and implement new features for Google AI products used by millions of people around the world.
- Collaborate with Google AutoML, Google Cloud AI and Google Brain teams.
Research Intern
- Research in data science, NLP and social media mining focusing on misinformation and fake news in social media.
- Collaborate with researchers from CNN and University of Michigan to conduct and weekly report our analysis about the US election at The Breakthrough.
Teaching Assistant
- COSC-282 Big Data Analytics (Undergraduate Level - Spring 2018)
- COSC-287 Introduction to Data Science (Undergraduate Level - Fall 2019)
- COSC-587 Introduction to Data Analytics (Graduate Level - Fall 2021)
Research Assistant
- Advise student research groups working on social media mining projects.
- Conduct research funded by Massive Data Institute (MDI) and National Science Foundation (NSF).
Software Engineer
- Gather requirements, design, development, testing and validation using Ruby on Rails.
- Develop APIs to reduce back-office operation time by 75% including PDF bill generation, email confirmation, bank account notification for Slack, etc.
- Research in Neuroscience and Machine Learning mainly using MATLAB and C++. The advisor is Prof. Masayuki Numao.
- Collaboratively conduct experiments with the Biochemical Lab (Nagai Lab).
- Develop APIs to collect streaming data from EEG brainwave headset in C++ and apply ML models to evaluate user’s emotions.
Research Assistant
- A member of Machine Intelligence and Knowledge Discovery Lab (MIND Lab).
- Conducting research to solve data science problems in real-world including wind power prediction from power plants (time series), emotion prediction from brain wave (neuroscience and ML/AI) and analysis of course materials (text mining).
Publications
(2022).
DeMis: Data-efficient Misinformation Detection using Reinforcement Learning.
In ECML-PKDD.
(2022).
PoliBERTweet: A Pre-trained Language Model for Analyzing Political Content on Twitter.
In LREC.
(2022).
Inferring #MeToo Experience Tweets Using Classic and Neural Models.
In DATA.
(2022).
Traditional and Context-specific Spam Detection in Low Resource Settings.
In Machine Learning.
(2021).
Research note: Lies and presidential debates: How political misinformation spread across media streams during the 2020 election.
In HKS Misinformation Review.
Related Courses
Graduate-level
- Algorithms
- Machine Learning
- Neural Networks and Deep Learning
- Text Mining & Analysis
- Intro to Data Analytics
- Massive Data Fundamentals
- Web Search and Sense Making (Scala)
- Dialogue Systems
- Algorithms for Distributed Machine Learning (Ph.D. Seminar)
- Distributed Algorithms and Systems (Ph.D. Seminar)
- Data Protection by Design (Ph.D. Seminar)
- Deep Reinforcement Learning (Ph.D. Sit-in)
Undergraduate-level
- Algorithm Design
- Artificial Intelligence
- Software Engineering
- Auto Speech Recognition
- Time Series Mining
- Web Development
- Statistics for Physical Science
- Data Structure (C++)
- Programming Method (JAVA)
- Distributed System Essential
- System Analysis and Design
- Computer Security
- Database Design
- Computer Network
- Computer Graphic
Contact
- kornraphop.k [at] gee-mail